Breaking Down AdWords Attribution Models
Understanding the customer journey is fundamental for brands to compete online today. Yet despite its importance, true attribution in digital marketing can be an extremely cumbersome undertaking. When it comes to paid media channels such as Facebook ads, programmatic display and of course, PPC, choosing the right attribution model can make all the difference in understanding the customer journey.
In the past 2 years, there have been several enhancements to the newly re-branded Google Ads platform in terms of modeling options when setting up conversions.
Each different option caters to different growth strategies and can have very different results depending on what you choose to go with.
Throughout this post, we’ll explain each different model available in Google Ads and provide examples of why you would pick one of the other depending on your goals.
Let’s look at the different attribution models available to us directly in the Google Ads engine. Here’s Google’s official explanation:
- Last Click: Gives all credit for the conversion to the last-clicked ad and corresponding keyword.
- First Click: Gives all credit for the conversion to the first-clicked ad and corresponding keyword.
- Linear: Distributes the credit for the conversion equally across all clicks on the path.
- Time Decay: Gives more credit to clicks that happened closer in time to the conversion. Credit is distributed using a 7-day half-life. In other words, a click 8 days before a conversion gets half as much credit as a click 1 day before a conversion.
- Position-Based: Gives 40% of credit to both the first- and last-clicked ads and corresponding keyword, with the remaining 20% spread out across the other clicks on the path.
- Data-Driven: Distributes credit for the conversion based on past data for this conversion action. (This is only available to accounts with enough data.) Data-driven attribution is different from the other attribution models, in that it uses your conversion data to calculate the actual contribution of each keyword across the conversion path. Each data-driven model is specific to each advertiser. It’s also important to keep in mind, however, that attribution modeling is only available for Search Network and Shopping clicks and isn’t available for interactions with GDN campaigns.
A customer finds your sports shoes website by clicking on your ads after performing each of these searches: “orthopedic shoes,” “running shoes,” “comfortable running shoes,” and then “comfortable orthopedic running shoes.” They make a purchase after clicking on your ad that appeared with “comfortable orthopedic running shoes.”
- In the “Last click” attribution model, the last keyword, “comfortable orthopedic running shoes,” would receive 100% of the credit for the conversion.
- In the “First click” attribution model, the first keyword, “orthopedic shoes,” would receive 100% of the credit for the conversion.
- In the “Linear” attribution model, each keyword would share equal credit (25% each) for the conversion.
- In the “Time decay” model, “comfortable orthopedic running shoes” would receive the most credit because it was searched closest to the conversion. The “orthopedic shoes” keyword would receive the least credit since it was the furthest from the conversion.
- In the “Position-based” model, “orthopedic shoes” and “comfortable orthopedic running shoes” would each get 40% credit, while “running shoes” and “comfortable running shoes” would each get 10% credit.
- In the “Data-driven” attribution model, each keyword would be attributed part of the credit, depending on how much it contributed to driving the conversion.
Last Click: Most advertisers and PPC managers are familiar with this model and is the standard. The pros are that it allows you to maximize your PPC efficiency but it severely undermines other channels in the conversion path and can overvalue brand search and remarketing. You would want to choose this model if your growth strategy is more on the conservative side.
First Click: This would be the exact opposite of the one above and gives all credit to the first interaction. The benefits of this model is that it gives credit to your top of funnel efforts which can lead to more customer acquisition in the long term. One drawback however, is that it might make very broad competitive terms look more profitable.
Linear: If first and last click models are too finite for your business, you might consider linear attribution. In this model, all clicks that lead to the conversion are given the same amount of credit]. Here, every touch point is considered which caters to a moderate growth strategy.
Time Decay: This model is conservative and gives more credit to clicks that happened closer in time to the conversion. Credit is distributed using a 7-day half-life. In other words, a click 8-days before a conversion gets half as much credit as a click 1-day before a conversion. I tend to like this model a lot because it can provide efficiency at the bottom of the funnel while still giving credit to the top of funnel. The downside of this one, similar to last click, is that it might overvalue brand and remarketing.
Position Based: This model can undervalue touchpoints at the middle of the funnel since it gives most credit to the first and last interactions. This can be detrimental to brands with long sales cycles as they can have a less clear understanding of those minor touch points that eventually lead to conversions.
The good news for marketers is that Google Ads is equipped with an Attribution Modeling report that allows you to what the various models say about your data, without actually making a change to your default reporting. This attribution reports lets you compare two different attribution models side-by-side.
So what’s the best attribution model to choose from? The answer to that is… it depends! Each industry and brand is different so there is no golden rule on what to do. Using these attribution models will help you identify which parts of your campaigns are contributing to overall revenue and even though they may not be bringing in direct conversions.